我有一个Python命令行程序,需要一段时间才能完成。我想知道完成跑步所需的确切时间。
我看过timeit模块,但它似乎只适用于小代码片段。我想给整个节目计时。
我有一个Python命令行程序,需要一段时间才能完成。我想知道完成跑步所需的确切时间。
我看过timeit模块,但它似乎只适用于小代码片段。我想给整个节目计时。
当前回答
我认为这是最好和最简单的方法:
from time import monotonic
start_time = monotonic()
# something
print(f"Run time {monotonic() - start_time} seconds")
或与装饰师一起:
from time import monotonic
def record_time(function):
def wrap(*args, **kwargs):
start_time = monotonic()
function_return = function(*args, **kwargs)
print(f"Run time {monotonic() - start_time} seconds")
return function_return
return wrap
@record_time
def your_function():
# something
其他回答
我喜欢datetime模块提供的输出,其中时间增量对象以人类可读的方式显示天、小时、分钟等。
例如:
from datetime import datetime
start_time = datetime.now()
# do your work here
end_time = datetime.now()
print('Duration: {}'.format(end_time - start_time))
样本输出,例如。
Duration: 0:00:08.309267
or
Duration: 1 day, 1:51:24.269711
正如J.F.Sebastian所提到的,这种方法在当地时间可能会遇到一些棘手的情况,因此使用更安全:
import time
from datetime import timedelta
start_time = time.monotonic()
end_time = time.monotonic()
print(timedelta(seconds=end_time - start_time))
在Linux或Unix中:
$ time python yourprogram.py
在Windows中,请参阅StackOverflow问题:如何在Windows命令行上测量命令的执行时间?
对于更详细的输出,
$ time -v python yourprogram.py
Command being timed: "python3 yourprogram.py"
User time (seconds): 0.08
System time (seconds): 0.02
Percent of CPU this job got: 98%
Elapsed (wall clock) time (h:mm:ss or m:ss): 0:00.10
Average shared text size (kbytes): 0
Average unshared data size (kbytes): 0
Average stack size (kbytes): 0
Average total size (kbytes): 0
Maximum resident set size (kbytes): 9480
Average resident set size (kbytes): 0
Major (requiring I/O) page faults: 0
Minor (reclaiming a frame) page faults: 1114
Voluntary context switches: 0
Involuntary context switches: 22
Swaps: 0
File system inputs: 0
File system outputs: 0
Socket messages sent: 0
Socket messages received: 0
Signals delivered: 0
Page size (bytes): 4096
Exit status: 0
我使用了一个非常简单的函数来计时代码执行的一部分:
import time
def timing():
start_time = time.time()
return lambda x: print("[{:.2f}s] {}".format(time.time() - start_time, x))
要使用它,只需在代码之前调用它来度量以检索函数计时,然后在代码之后调用带有注释的函数。时间将显示在评论前面。例如:
t = timing()
train = pd.read_csv('train.csv',
dtype={
'id': str,
'vendor_id': str,
'pickup_datetime': str,
'dropoff_datetime': str,
'passenger_count': int,
'pickup_longitude': np.float64,
'pickup_latitude': np.float64,
'dropoff_longitude': np.float64,
'dropoff_latitude': np.float64,
'store_and_fwd_flag': str,
'trip_duration': int,
},
parse_dates = ['pickup_datetime', 'dropoff_datetime'],
)
t("Loaded {} rows data from 'train'".format(len(train)))
然后输出将如下所示:
[9.35s] Loaded 1458644 rows data from 'train'
使用line_profiler。
line_profiler将描述单个代码行执行所需的时间。分析器通过Cython在C语言中实现,以减少分析开销。
from line_profiler import LineProfiler
import random
def do_stuff(numbers):
s = sum(numbers)
l = [numbers[i]/43 for i in range(len(numbers))]
m = ['hello'+str(numbers[i]) for i in range(len(numbers))]
numbers = [random.randint(1,100) for i in range(1000)]
lp = LineProfiler()
lp_wrapper = lp(do_stuff)
lp_wrapper(numbers)
lp.print_stats()
结果将是:
Timer unit: 1e-06 s
Total time: 0.000649 s
File: <ipython-input-2-2e060b054fea>
Function: do_stuff at line 4
Line # Hits Time Per Hit % Time Line Contents
==============================================================
4 def do_stuff(numbers):
5 1 10 10.0 1.5 s = sum(numbers)
6 1 186 186.0 28.7 l = [numbers[i]/43 for i in range(len(numbers))]
7 1 453 453.0 69.8 m = ['hello'+str(numbers[i]) for i in range(len(numbers))]
time.clock在Python 3.3中已被弃用,并将从Python 3.8中删除:请改用time.perf_counter或time.prrocess_time
import time
start_time = time.perf_counter ()
for x in range(1, 100):
print(x)
end_time = time.perf_counter ()
print(end_time - start_time, "seconds")